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WORLD INTELLECTUAL PROPERTY ORGANIZATION 
International Bureau 




PCT 

INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) 



(51) International Patent Classification 7 : 




(11) International Publication Number: 


WO 00/39707 


G06F 17/30 


Al 










(43) International Publication Date: 


6 July 2000 (06.07.00) 



(21) International Application Number: PCT/EP99/10221 

(22) International Filing Date: 15 December 1999 (15.12.99) 



(30) Priority Data: 
09/220,277 



23 December 1 998 (23. 1 2.98) US 



(71) Applicant: KONINKLIJKE PHILIPS ELECTRONICS N.V. 

[NL/NL]; Groenewoudseweg 1, Nl-5621 BA Eindhoven 
(NL). 

(72) Inventors: ELENBAAS, Jan, H.; Prof. Holstlaan 6, Nl-5656 

AA Eindhoven (NL). DIMTTROVA, Nevenka; Prof. Hol- 
stlaan 6, Nl-5656 AA Eindhoven (NL). MCGEE, Thomas; 
Prof. Holstlaan 6, Nl-5656 AA Eindhoven (NL). SIMP- 
SON, Markf Prof. Holstlaan 6, Nl-5656 AA Eindhoven 
(NL). MARTINO, Jacquelyn, A.; Prof. Holsdaan 6, 
Nl-5656 AA Eindhoven (NL). ABDEL-MOTTALEB, Mo- 
hamcd ; Pro f. Holstlaan 6. Nl-5656 AA Eindhoven (NL). 
GARRETT, Marjorie; Prof. Holstlaan 6, Nl-5656 AA 
Eindhoven (NL). RAMSEY, Carolyn; Prof. Holstlaan 6, 
Nl-5656 AA Eindhoven (NL). DESAI. Ranjit; Prof. Holst- 
laan 6, Nl-5656 AA Eindhoven (NL). 



(74) Agent: GROENENDAAL, Antonius, W., M.; Internationaal 
Octrooibureau B.V., Prof. Holstlaan 6, NL-5656 A A 
Eindhoven (NL). 



(81) Designated States: CN, JP, KR, European patent (AT, BE, CH, 
CY, DE, DK, ES, FT, FR, GB. GR, IE, IT, LU, MC, NL, 
PT, SE). 



Published 

With international search report. 



(54) Title: PERSONALIZED VIDEO CLASSIFICATION AND RETRIEVAL SYSTEM A 
(57) Abstract 

A video retrieval system is presented that allows a user to quickly and easily select and receive stories of interest from a video 
stream. The video retrieval system classifies stories and delivers samples of selected stories that match each user's current preference. The 
user s preferences may include particular broadcast networks, persons, story topics, keywords, and the like. Key frames of each selected 
story are sequentially displayed; when the user views a frame of interest, the user selects the story that is associated with the key frame for 
more detailed viewing. This invention is particularly well suited for targeted news retrieval. In a preferred embodiment, news stories are 
stored, and the selection of a news story for detailed viewing based on the associated key frames effects a playback of the selected news 
story. The principles of this invention also allows a user to effect a directed search of other types of broadcasts as well For example 
the user may initiate an automated scan that presents samples of broadcasts that conform to the user's current preferences, akin to directed 
channel-surfing. 



FOR THE PURPOSES OF INFORMATION ONLY 
Codes used to identify States party to the PCT on the front pages of pamphlets publishing international applications under the PCT. 



AL 


Albania 


ES 


AM 


Armenia 


n 


AT 


Austria 


FR 


AU 


Australia 


GA 


AZ 


Azerbaijan 


GB 


BA 


Bosnia and Herzegovina 


GE 


DB 


Barbados 


GH 


BE 


Belgium 


GN 


BF 


Burkina Faso 


GR 


BG 


Bulgaria 


HI) 


BJ 


Benin 


IE 


BR 


Brazil 


IL 


BY 


Belarus 


IS 


CA 


Canada 


IT 


CF 


Central African Republic 


JP 


CC 


Congo 


KE 


CI) 


Switzerland 


KG 


CI 


Cote d' I voire 


KK 


CM 


Cameroon 




CN 


China 


KR 


CU 


Cuba 


KZ 


CZ 


Czech Republic 


LC 


DE 


Germany 


U 


DK 


Denmark 


LK 


EE 


Estonia 


LR 



Spain 
Finland 
France 
Gabon 

United Kingdom 

Georgia 

Ghana 

Guinea 

Greece 

Hungary 

Ireland 

Israel 

Iceland 

Italy 

Japan 

Kenya 

Kyrgyzstan 

Democratic People's 

Republic of Korea 

Republic of Korea 

Kazakstan 

Saint Lucia 

Liechtenstein 

Sri Lanka 

Liberia 



LS 
LT 
LU 
LV 
MC 
MD 
MG 
MK 

ML 

MN 

MR 

MW 

MX 

NR 

NL 

NO 

NZ 

PL 

PT 

RO 

RU 

SD 

SE 

SG 



Lesotho 


SI 


Slovenia 


Lithuania 


SK 


Slovakia 


Luxembourg 


SN 


Senegal 


Latvia 


sz 


Swaziland 


Monaco 


TD 


Chad 


Republic of Moldova 


TG 


Togo 


Madagascar 


TJ 


Tajikistan 


The former Yugoslav 


TM 


Turkmenistan 


Republic of Macedonia 


TR 


Turkey 


Mali 


TT 


Trinidad and Tobago 


Mongolia 


UA 


Ukraine 


Mauritania 


UG 


Uganda 


Malawi 


US 


United States of America 


Mexico 


uz 


Uzbekistan 


Niger 


VN 


Viet Nam 


Netherlands 


YU 


Yugoslavia 


Norway 


zw 


Zimbabwe 



New Zealand 
Poland 
Portugal 
Romania 

Russian Federation 

Sudan 

Sweden 

Singapore 



WO 00/39707 B ^§ PCT/EP99/10221 

1 

PERSONALIZED VIDEO CLASSIFICATION AND RETRIEVAL SYSTEM 



Background of the Invention 

1. Field of the Invention 

This invention relates to the field of communications and information 
processing, and in particular to the field of video categorization and retrieval. 

2. Description of Related Art 

Consumers are being provided an ever increasing supply of information and 
entertainment options. Hundreds of television channels are available to consumers, via 
broadcast, cable, and satellite communications systems. Because of the increasing supply of 
information, it is becoming increasingly more difficult for a consumer to efficiently select 
information sources that provide information of particular or specific interest. Consider, for 
example, a consumer who randomly searches among dozens of television channels ("channel 
surfs") for topics of interest to that consumer. If a topic of specific interest to the consumer is 
not a popular topic, only one or two broadcasters are likely to broadcast a story dealing with 
this topic, and only for a short duration. Unless the consumer is advised beforehand, it is 
unlikely that the consumer having the interest will be tuned to the particular broadcasters' 
channel when the story of interest is broadcast. Conversely, if the topic of interest is very 
popular, many broadcasters will broadcast stories dealing with the topic, and the channel- 
surfing consumer will be inundated with redundant information. 

Automated scanning is commonly available for radio broadcasts, and somewhat 
less commonly available for television broadcasts. Traditionally, these scans provide a short 
duration sample of each broadcast channel. If the user selects the channel, the tuner remains 
tuned to that channel; otherwise, the scanner steps to the next found channel. This scanning, 
however, is neither directed nor selective. No assistance is provided, for example, for the user 
to scan specifically for a news station on a radio, or a sports show on a television. Each found 
channel will be sampled and presented to the user, independent of the user's current interests. 

The continuing integration of computers and television provides for an 
opportunity for consumers to be provided information of particular interest. For example, 
many web sites offer news summaries with links to audio-visual and multimedia segments 



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^ 2 

corresponding to current news stories. The sorting and presentation of these news summaries 

can be customized for each consumer. For example, one consumer may want to see the 

weather first, followed by world news, then local news, whereas another consumer may only 

want to see sports stories and investment reports. The advantage of this system is the 

5 customization of the news that is being presented to the user; the disadvantage is the need for 

someone to prepare the summary, and the subsequent need for the consumer to read the 

summary to determine whether the story is worth viewing. 

Advances are being made continually in the field of automated story 

segmentation and identification, as evidenced by the BNE (Broadcast News Editor) and BNN 

10 (Broadcast News Navigator) of the MITRE Corporation (Andrew Merlino, Daryl Morey, and 
Mark Maybury, MITRE Corporation, Bedford MA, Broadcast News Navigation using Story 
Segmentation, ACM Multimedia Conference Proceedings, 1997, pp. 381-389). Using the 
BNE, newscasts are automatically partitioned into individual story segments, and the first line 
of the closed-caption text associated with the segment is used as a summary of each story. Key 

15 words from the closed-caption text or audio are determined for each story segment. The BNN 
allows the consumer to enter search words, with which the BNN sorts the story segments by 
the number of keywords in each story segment that match the search words. Based upon the 
frequency of occurrences of matching keywords, the user selects stories of interest. Similar 
search and retrieval techniques are becoming common in the art. For example, conventional 

20 text searching techniques can be applied to a computer based television guide, so that a person 
may search for a particular show title, a particular performer, shows of a particular type, and 
the like, 

A disadvantage of the traditional search and retrieval techniques is the need for 
an explicit search task, and the corresponding selection among alternatives based upon the 

25 explicit search. Often, however, a user does not have an explicit search topic in mind. In a 
typical channel-surfing scenario, a user does not have an explicit search topic. A channel- 
surfing user randomly samples a variety of channels for any of a number of topics that may be 
of interest, rather than specifically searching for a particular topic. That is, for example, a user 
may initiate a random sampling with no particular topic in mind, and select one of the many 

30 channels sampled based upon the topic that was being presented on that channel at the time of 
sampling. In another scenario, a user may be monitoring the television in a "background" 
mode, while performing another task, such as reading or cooking. When a topic of interest 
appears, the user redirects his focus of interest to the television, then returns his attention to 
the other task when a less interesting topic is presented. 



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Brief Summary of the Invention 

It is an object of this invention to provide a news retrieval system that allows a 
user to quickly and easily select and receive stories of interest. It is a further object of this 
invention to identify broadcasts of potential interest to a user, and to provide a random or 
systematic sampling of these broadcasts to the user for subsequent selection. 

These objects and others are achieved by providing a system that characterizes 
news stories and delivers samples of selected news stories that match each user's current 
preference. The user's'preferences may include particular broadcast networks, anchor persons, 
story topics, keywords, and the like. Key frames of each selected news story are sequentially 
displayed; when the user views a frame of interest, the user can select the news story that is 
associated with the key frame for detailed viewing. In a preferred embodiment, the news 
stories are stored, and the selection of a news story for detailed viewing effects a playback of 
the selected story. 

Although this invention is particularly well suited for targeted news retrieval, 
the principles of this invention also allows a user to effect a directed search of other types of 
broadcasts as well. For example, the user may initiate an automated scan that presents samples 
of broadcasts that conform to the user's current preferences, akin to directed channel-surfing. 

Brief Description of the Drawings 

FIG. 1 illustrates an example block diagram of a personalized video search 
system in accordance with this invention. 

FIG. 2 A illustrates an example video stream 200 of a news broadcast. 

V 

FIG. 2B illustrates the extraction of key frames from a story segment of a video 
stream in accordance with this invention. 

FIG. 3 illustrates an example user interface for a video retrieval system in 
accordance with this invention. 

FIG. 4 illustrates an example block diagram of a consumer product 400 in 
accordance with this invention. 

Detailed Description of the Invention 

FIG. 1 illustrates an example block diagram of a personalized video search 
system in accordance with this invention. The video retrieval system consists of a 
classification system 100 that classifies each segment of a video stream and a retrieval system 



WO 00/39707 S A PCT/EP99/10221 

4 

150 that selects and displays segments that match one or more user preferences. The video 
retrieval system receives a video stream 101 from a broadcast channel selector 105, for 
example a television tuner or satellite receiver. The video stream may be in digital or analog 
form, and the broadcast may be any form or media used to communicate the video stream, 
5 including point to point communications. For clarity and ease of understanding, the example 
video search system presented herein will be presented in the context of a search system for 
news stories conforming to a set of user preferences, although the extension of the principles 
presented herein to other video search applications will be evident to one of ordinary skill in 
the art. 

10 The example classification system 100 of FIG. 1 includes a story segment 

identifier 110, a classifier 120, and a visual characterizer 130. The story segment identifier 110 
processes a video stream 101 and identifies discrete segments 1 1 1 of the video stream 101. In 
the example context, the video stream 101 corresponds to a news broadcast, and includes 
multiple news stories with interspersed advertisements, or commercials. The story segment 

15 identifier 1 10 partitions the video stream 101 into news story segments 111, either by copying 
each discrete story segment 111 from the video stream 101 to a storage device 1 15, or by 
forming a set of location parameters that identify the beginning and end of each discrete story 
segment 1 1 1 on a copy of the video stream 101 . As illustrated by the dotted line 106, in a 
preferred embodiment, the video stream 101 is stored on a storage device 115 that allows for 

20 the replay of segments 1 1 1 based on the location of the segments 1 1 1 on the medium, such as 
a video tape recorder, laser disc, DVD, DVR, CD-RAV, computer file system, and the like. For 
ease of understanding, the invention is presented as having the story segments 1 1 1 stored on 
the storage device 1 15. As would be evident to one of ordinary skill in the art, this is 
equivalent to recording the entire video stream 101 and indexing each story segment 111 

25 relative to the video stream 101 . 

The story segments 1 1 1 are identified using a variety of techniques. The typical 
news broadcast follows a common format that is particularly well suited for story 
segmentation. FIG. 2A illustrates an example video stream 200 of a news broadcast. After an 
introduction 201, a newsperson, or anchor, appears 211 and introduces the first news story 

30 segment 221. After the first news story segment 221 is complete, the anchor reappears 212 to 
introduce the next story segment 222. After the story segment 222 is complete, there is a cut 
218 to a commercial 228. After the commercial 228, the anchor reappears 213 and introduces 
the next story segment 223. This sequence of anchor-story, interspersed with commercials, 
repeats until the end of the news broadcast. 



10 



WO 00/39707 A M PCT/EP99/10221 

^ 5 

The repeated appearances 21 1-214 of the anchor, typically in the same staged 
location serves to clearly identify the start of each news segment and the end of the prior news 
segment or commercial. Techniques are commonly available to identify commercials in a 
video stream, as used for example in devices that mute the sound when a commercial appears. 
Commercials 228 may also occur within a story segment 222. The cut 218 to a commercial 
228 may also include a repeated appearance of the anchor, but the occurrence of the 
commercial 228 serves to identify the appearance as a cut 218, rather than an introduction to a 
new story segment. The anchor may appear within the broadcast of the story segments 221- 
224, but most broadcasters use one staged location for story introductions, and different staged 
appearances for dialog shots or repeated appearances after a commercial. For example, the 
anchor is shown sitting at the news desk for a story introduction, then subsequent images of 
the newscaster are close ups, without the news desk in the image. Or, the anchor is presented 
full screen to introduce the story, then on a split screen when speaking with a field reporter. 
Or, the anchor shot is full facial to introduce a story, and profiled within the story. Once the 
15 characteristic story-introduction image is identified, image matching techniques common in 
the art can be used to automate the story segmentation process. In situations that do not have 
story segmentation breaks that lend themselves to automated story segmentation, manual or 
semi-automated techniques may be used as well. Also, as standards such as MPEG are 
developed for customizable video composition and splicing, it can be expected that video 
20 streams will contain explicit markers that identify the start and end of independent segments 
within the streams. I 

Also associated with the video stream is an audio stream 230 and, in many 
cases, a closed caption text stream 240 corresponding to the audio stream 230. Each story 
segment 221-224 of FIG. 2A has an associated audio segment 231-234, and possibly closed 
25 caption text 241-244. The audio segments 231-234 are synchronous with the video segments, 
and may be included within each story segment 221-224. Due to the differing transmission 
times of audio and text, the closed caption text segments 241-244 do not necessarily consume 
the same time span as the audio segments 231-234. The story segment identifier 110 may also 
include a speech recognition device that creates text segments 241-244 corresponding to each 
30 audio segment 23 1-234. 

In addition to the transcripts of the audio segments, the text segments 241-244 
include text from other sources as well. For example, in a non-news broadcast, a television 
guide may be available that provides a synopsis of each story, a list of characters, a reviewer's 
rating, and the like. In a news broadcast, an on-line guide may be available that provides a list 



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of headlines, a list of newscasters, a list of companies or people contained in the broadcast, 
and the like. Also associated with each broadcast and each story segment are textual 
annotations indicating the broadcast channel being monitored by the broadcast channel 
selector 105, such as "ABC", "NBC*, "CNN", etc., as well as the name of each anchor 
introducing each story. The anchor's name may be automatically determined based on image 
recognition techniques, or manually determined. Other annotations may include the time of the 
broadcast, the locale of each story, and so on. In a preferred embodiment of this invention, 
each of these text formatted information segments will be associated with their corresponding 
story segment. Teletext formatted data may also be included in text segment 241-244. 

The story segments 221-224, audio segments 231-234, and text segments 241- 
244 of FIG. 2A correspond to the story segments 111, audio segments 1 12, and text segments 
1 13 from the story segment identifier 1 10 of FIG. 1, and the video 228, audio 238 and text 248 
segments correspond to a commercial. 

FIG. 2B illustrates the extraction of key frames from a story segment of a video 
stream in accordance with one aspect of this invention. The story segment 221 includes a 
number of scenes 251-253. For example, the first scene 251 of story segment 221 corresponds 
to the image 21 1 of the anchor introducing the story segment 221. The next scene 252 may be 
images from a remote camera covering the story, and so on. Each scene consists of frames. 
The first frame 261, 271, 281 of each scene 251, 252, 253 forms a set of key frames 291, 292, 
293 associated with the story segment 221, the key frames forming a pictorial summary of the 
story segment 221. The key frames 291, 292, 293 of FIG. 2B correspond to the key frames 114 
from the story segment identifier 1 10 of FIG. 1. 

The first frame of each scene can be identified based upon the differences 
between frames. As the anchor moves during the introduction of the story, for example, only 
slight differences will be noted from frame to frame. The region of the image corresponding to 
the news desk, or the news room backdrop, will not change substantially from frame to frame. 
When a scene change occurs, for example by switching to a remote camera, the entire image 
changes substantially. A number of image compression or transform schemes provide for the 
ability to store or transmit a sequence of images as a sequence of difference frames. If the 
differences are substantial, the new frames are typically encoded directly as reference frames; 
subsequent frames are encoded as differences from these reference frames. FIG. 2B illustrates 
such a scheme by the relative size of each frame F in each scene 251-253. The first frame 261, 
271, 281 of each scene 251, 252, 253 are encoded as reference frames, containing a substantial 
amount of information, or encoded as difference frames containing a substantial number of 



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differences from their prior frames. After the change of scenes, subsequent frames are smaller, 
reflecting the same overall scene with minor changes caused by the movement of the objects 
in the frame or changes to the camera angle or magnification. The amount of information 
contained in each frame is directly related to the changes from one frame to the next. In the 
5 MPEG compression scheme, for example, images are transformed using a Discrete Cosine 
Transformation (DCT), which produces an encoding of each frame having a size that is 
strongly correlated to the amount of random change from one frame to the next. That is, for 
example, frames 262, 263, and 264 are shown to be substantially smaller than frame 261, 
because they contain less information than frame 261, which is the frame corresponding to a 

10 scene change. Thus, in a preferred embodiment of this invention, the key frames 291, 292, 293 
correspond to the frames containing the most information 261, 271, 281 in the story segment 
221. Other techniques of selecting key frames would be evident to one of ordinary skill in the 
art. For example, one could choose the frame from the center of each scene, or choose the 
frame having the least difference from all the other frames in the scene, using for example a 

15 least squares determination, and the like. As in the case of story segmentation, manual and 
semi-automated techniques may also be employed to select key frames, the composite of 
which form a pictorial summary of each story segment. Also as in the case of story 
segmentation, future encoding standards may include a direct indication of such key frames in 
each story segment. 

i 

20 The classifier 120 characterizes each story segment 1 1 1 of FIG. L In a 

preferred embodiment, the classifier 120 effects the characterization automatically, although 
manual or semi-automated techniques may be used as well. The primary means of 
characterization in the preferred embodiment is based on the text segments 113 from the story 
segment identifier 1 10. If the text segments 1 13 include annotations such as the broadcast 

25 channel and the anchor's name, these annotations are used to identify the story segment in 
corresponding "broadcaster" and "anchor" categories. If the text segments 113 are 
transcriptions or summaries of the story segment, keywords such as "victijn", "police", 
"crime", "defendant", and the like are used to characterize a news story under the topic of 
"crime". Keywords such as "democrat", "republican", "house", "senate", "prime minister", 

30 and the like are used to characterize a news story under the topic of "politics". Sub 

categorizations can also be defined, such that "home run" characterizes a story as sub category 
"baseball" under category "sports", while "touch down" characterizes a story as sub category 
"football" under the same category "sports". Similarly, particular names, such as "Clinton", 
"Bill Gates", "John Wayne" are used to categorize stories as "politics", "computers", 



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"entertainment", respectively. A story segment may have multiple categorizations; for 
example, "Bill Gates" may be used to categorize stories as both "computers" and "finance". 
Similarly, the presence of "defendant" and "democrat" in the same story causes the story to be 
categorized as both "crime" and "politics". In like manner, the audio segments 112 may be 
5 used for categorization. In an indirect manner, the audio segments 1 12 may be converted to 
text and the categorization applied to the text In a direct manner, the audio segments 1 12 may 
be analyzed for sounds of laughter, explosions, gunshots, cheers, and the like to determine 
appropriate characterizations, such as "comedy", "violence", and "celebration". 

Optionally, a visual characterizer 130 characterizes story segments 111 based 

10 on their visual content. The visual characterizer 130 may be used to identify people appearing 
in the story segments, based on visual recognition techniques, or to identify topics based on an 
analysis of the image background information. For example, the visual characterizer 130 may 
include a library of images of noteworthy people. The visual characterizer 130 identifies 
images containing a single or predominant figure, and these images are compared to the 

15 images in the library. The visual characterizer 130 may also contain a library of context scenes 
and associated topic categories. For example, an image containing a person aside a map with 
isobars would characteristically identify the topic as "weather". Similarly, image processing 
techniques can be used to characterize an image as an "indoor" or "outdoor" image, a "city", 
"country", or "sea" locale, and so on. These visual characterizations 131 are provided to the 

20 classifier 120 for adding, modifying, or supplementing the categorizations formed from the 
text 1 13 and audio 1 12 segments associated with each story segment 1 1 1 . For example, the 
appearance of smoke in a story segment 1 1 1 may be used to refine a characterization of a siren 
sound in the audio segment 112 as Tire", rather than "police". 

The visual characterizer 130 may also be used to prioritize key frames. A 

25 newscast may have dozens or hundreds of key frames based upon a selection of each new 
scene. In a preferred embodiment, the number of key frames is reduced by selecting those 
images likely to contain more information than others. Certain image contents are indicative of 
images having significant content. For example, a person's name is often displayed below the 
image of the person when the person is first introduced during a newscast. This composite 

30 image of a person and text will, in general, convey significant inforrnation'regarding the story 
segment 1 1 1 . Similarly a close-up of a person or small group of people will generally be more 
informative than a distant scene, or a scene of a large group of people. A number of image 
analysis techniques are commonly available for recognizing figures, flesh tones, text, and 
other distinguishing features in an image. In a preferred embodiment, key frames are 



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prioritized by such image content analysis, as well as by other cues, such as the chronology of 
scenes. In general, the more important scenes are displayed earlier in the story segment 111 
than less important scenes. The prioritization of key frames is also used to create a visual table 
of contents for the story segments 1 1 1, as well as for a visual table of contents for the video 
stream 101, by selecting a given number frames in priority order. 

The classification system 100 provides the set of characterizations, or 
classification 121, of each story segment 1 1 1 from the classifier 120, and the set of key frames 
114 for each story segment 111 from the story segment identifier 110, to the retrieval system 
150. The classification 121 may be provided in a variety of forms. Predefined categories such 
as "broadcaster", "anchor", "time", "locale", and "topic" are provided in the preferred 
embodiment, with certain categories, such as "locale" and "topic" allowing for multiple 
entries. Another method of classification that is used in conjunction with the predefined 
categories is a histogram of select keywords, or. a list of people or organizations mentioned in 
the story segment 111. The classification 121 used in the classification system 100 should be 
consistent or compatible with, albeit not necessarily identical to, the filtering system used in 
the filter 160 of the retrieval system 150. As would be evident to one of ordinary skill in the 
art, a classification translator can be appended between the classification system 100 and 
retrieval system 150 to convert the classification 121, or a portion of the classification 121, to 
a form that is compatible with the filtering system used in the filter 160. This translation may 
be automatic, manual, or semi-automated. For ease of understanding, it is assumed herein that 
the classification 121 of each story segment 111 by the classification system 100 is compatible 
with the filter 160 of the retrieval system 150. <" 

The filter 160 of the retrieval system 150 identifies the story segments 111 that 
conform to a set of user preferences 191, based on the classification 121 of each of the story 
segments 1 1 1. In a preferred embodiment of this invention, the user is provided a profiler 190 
that encodes a set of user input into preferences 191 that are compatible with the filtering 
system of the filter 160 and compatible with the classification 121. For example, if the 
classification 121 includes an identification of broadcast channels or anchors, the profiler 190 
will provide the user the option of specifying particular channels or anchors for inclusion or 
exclusion by the filter 160. In a preferred embodiment, the profiler 190 includes both 
"constant" as well as "temporal" preferences, allowing the user to easily modify those 
preferences that are dependent upon the user's current state of mind while maintaining a set of 
overall preferences. In the temporal set, for example, would be a choice of topics such as 
"sports" and "weather". In the constant set, for example, would be a list of anchors to exclude 



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regardless of whether the anchor was addressing the current topic of interest. Similarly, the 
constant set may include topics such as "baseball" or "stock market", which are to be included 
regardless of the temporal selections. Consistent with common techniques used for searching, 
the profiler 190 allows for combinations of criteria using conjunctions, disjunctions, and the 
5 like. For example, the user may specify a constant interest in all "stock market" stories that 
contain one or more words that match a specified list of company names. 

The filter 160 identifies each of the story segments 1 1 1 with a classification 121 
that matches the user preferences 191. The degree of matching, or tightness of the filter, is 
controllable by the user. In the extreme, a user may request all story segments 1 1 1 that match 

10 any one of the user's preferences 191 ; in another extreme, the user may request all story 
segments 1 1 1 that match all of the user's preferences 191. The user may request all story 
segments 1 1 1 that match at least two out of three topic areas, and also contain at least one of a 
set of keywords, and so on. The user may also have negative preferences 191, such as those 
topics or keywords that the user does not want, for example "sports" but not "hockey". The 

15 filter 160 identifies each of the story segments 1 1 1 satisfying the user's preferences 191 as 
filtered segments 161. In a preferred embodiment, the filter 160 contains a sorter that ranks 
each story in dependence upon the degree of matching between the classification 121 and the 
user preferences 191, using for example a count of the number of keywords of each topic in 
each classification 121 of the story segments 111. For ease of understanding, the ranking 

20 herein is presented as a unidimensional, scalar quantity, although techniques for 

multidimensional ranking, or vector ranking, are common in the art. In the case of the same 
story being reported on multiple broadcast channels, the ranking 162 may be heavily weighted 
by the user's preferred anchor, or preferred broadcast channel; this ranking 162 may also be 
weighted by the time of each newscast, in preference to the most recent story. In a preferred 

25 embodiment, the user has the option to adjust the weighting factors. For example, the user may 
make a negative selection absolute: if the segment contains the negated topic or keyword, it is 
assigned the lowest rating, regardless of other matching preferences. Any number of common 
techniques can be used to effect such prioritization, including the use of artificial intelligence 
techniques such as knowledge based systems, fuzzy logic systems, expert systems, learning 

30 systems and the like. The filter 160 selects story segments 111 based on this ranking 162, and 
provides the ranking 162 of each of these selected, or filtered, segments 161 to the presenter 
170 of the retrieval system 150. 

In another embodiment of this invention, the filter 160 also identifies the 
occurrences of similar stories in multiple story segments, to identify popular stories, 



V 



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commonly called "top stories". This identification is determined by a similarity of 
classifications 121 among story segments 111, independent of the user's preferences 191. Hie 
similarity measure may be based upon the same topic classifications being applied to different 
story segments 1 1 1, upon the degree of correlation between the histograms of keywords, and 
so on. Based upon the number of occurrences of similar stories, the filter 160 identifies the 
most popular current stories among the story segments 111, independent of the user's 
preferences 191. Alternatively, the filter 160 identifies the most popular current stories having 
at least some commonality with the preferences 191. From these most popular current stories, 
the filter chooses one or more story segments 1 1 1 for presentation by the presenter 170, based 
upon the user's preferences 191 for broadcast channel, anchor person, and so on. 

In accordance with this invention, the presenter 170 presents the key frames 1 14 
of the filtered story segments 161 on a display 175. As discussed above, the set of key frames 
associated with each story segment 1 1 1 provides a pictorial summary of each story segment 
111. Thus, in accordance with this invention, the presenter 170 presents the pictorial summary 
171 of those story segments 161 which correspond to the user preferences 191. In a preferred 
embodiment, the number of key frames displayed for each story segment 161 is determined by 
the aforementioned prioritization schemes based on image content, chronology, associated 
text, and the like. Optionally, the presentation of the pictorial summary may be accompanied 
by the playing of portions of the audio segments that are associated with the story segment 
1 1 1 . For example, the portion of the audio segment may be the first audio segment of each 
story segment, corresponding to the introduction of the story segment by the anchor. In like 
manner, a summary of the text segment may also be displayed coincident with the display of 
the pictorial summary 171. When a particular filtered story segment's pictorial summary 171 
strikes the user's interest, the user selects the filtered story segment for full playback by a 
player 180 in the retrieval system 150. Common in the art, the user may effect the selection by 
pointing to the displayed key frames of the story of interest, using for example a mouse, or by 
voice command, gesture, keyboard input, and the like. Upon receipt of the user selection 176 
the player 180 displays the selected story segment 181 on the display 175. 

■FIG. 3 illustrates an example user interface for the retrieval system 150. The 
display 175 contains panes 310 for displaying filtered story segments key frames 171. As 
illustrated in FIG. 3, the display 175 includes four panes 310a, 310b, 310c and 310d, although 
fewer or more panes can be selected via the presenter controls 350. The presenter sequentially 
presents each of the key frames 171 in the panes 310. In a preferred embodiment, each of the 
key frames 171 corresponding to one story segment 161 are presented sequentially in one of 



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the panes 310a, 310b, 310c, or 310d. That is, in FIG. 3 the key frames of four story segments 
161 are displayed simultaneously, each pane providing the pictorial summary for each of the 
story segments 161. The user has the option of determining the duration of each key frame 
171, and whether the key frames 171 from a story segment 161 are repeated for a given time 
5 duration before the set of key frames 171 from another story segment 161 are presented in that 
pane. After all the key frames .1 14 of all the filtered story segments 161 are presented, the 
cycle is repeated, thereby providing a continuous slide show of the key frames of story 
segments that conform to the user's preferences. Alternative display methods can be 
employed. For example, four segments from a story segment 161 may be displayed in all four 

10 of the panes 3 10a-3 lOd simultaneously. Similarly, one pane may be defined as a primary pane, 
which is configured to contain the highest priority scene of the story segment 161 while the 
other panes sequentially display lower priority scenes. These and other techniques for video 
presentation will be apparent to one of ordinary skill in the art. In a preferred embodiment, 
presenter controls 350 are provided to facilitate the customization of the presentation and 

15 selection of key frames 171 . 

If the filter 160 provides a ranking 162 associated with each filtered story 
segment 161, the presenter 170 can use the ranking 162 to determine the frequency or duration 
of each presented set of key frames 171. That is, for example, the presenter 170 may present 
the key frames 1 14 of filtered segments 161 at a repetition rate that is proportional to the 

20 degree of correspondence between the filtered segments 161 and user preferences 191. 
Similarly, if a large number of filtered segments 161 are provided by the filter 160, the 
presenter 170 may present the key frames 1 14 of the segments 161 that have a high 
correspondence with the user preferences 191 at every cycle, but may present the key frames 
1 14 of the segments that have a low correspondence with the user preferences 191 at fewer 

25 than every cycle. 

The presenter controls 350 also allow the user to control the interaction between 
the presenter 170 and the player 180. In a preferred embodiment, the user can simultaneously 
view a selected story segment 181 in one pane 310 while key frames 171 from other story 
segments continue to be displayed in the other panes. Alternatively, the selected story segment 
30 181 may be displayed on the entire area of the display 175. These and other options for visual 
display are common to one of ordinary skill in the art. The user is also provided play control 
functions in 350 for conventional playback functions such as volume control, repeat, fast 
forward, reverse, and the like. Because the story segments 1 1 1 are partitioned into scenes in 



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the story segment identifier, the playback functions 350 may include such options as next 
scene, prior scene, and so on. 

The user interface to the profiler 190 is also provided via the display 175. In the 
example interface of FIG. 3, buttons 320 are provided to allow the user to set preferences 191 
5 in select categories. The "media" button 320a provides the user options regarding the 

broadcast channels, anchor persons, and the like. The "time" button 320b provides the user 
options regarding time settings, such as how far back in time the filter 160 should consider 
story segments. The "topics" button 320c allows the user to choose among topics, such as 
sports, art, finance, crime, etc. The "locale" button 320d allows the user to specify geographic 

10 areas of interest. The "top stories" button 320e allows the user to specify filter parameters that 
are to applied to the aforementioned identification of popular story segments. The "keywords" 
button 320f allows the user to identify specific keywords of interest. Other categories and 
options may also be provided, as would be evident to one of ordinary skill in the art. 

The user interface of FIG. 3 also allows for selection of presentation 330 and 

15 player 340 modes. The presenter 170 can be set to present key frames of story segments 

selected by the user's preference settings, or key frames of "top" story segments. The player 
180 can be set to operate in a browse mode, corresponding to the operation discussed above, 
wherein the user browses the key frames and selects story segments of interest; or in a play 
thru mode, wherein the player 180 presents each of the filtered story segments 161 in 

20 succession; and in a scan mode, wherein the player 180 presents the first scene of each filtered 
story segment 161 in succession. 

Other means of presenting key frames and associated materials can be provided. 
The presentation can be multidimensional, wherein, for example, the degree of correlation of a 
segment 111 to the user's preferences 191 identifies a depth, and the key frames are presented 

25 in a multidimensional perspective view using this depth to determine how far away from the 
user the key frames appear. Similarly, different categories 320 of user preferences can be 
associated with different planes of view, and the key frames of each segment having strong 
correlation with the user preferences in each category are displayed in each corresponding 
plane. These and other presentation techniques will be evident to one of ordinary skill in the 

30 art, in view of this invention. 

Although the invention has been presented primarily in the context of a news 
retrieval system, the principles presented herein will be recognized by one/of ordinary skill in 
the art to be applicable to other retrieval tasks as well. For example, the principles of the 
invention presented herein can be used for directed channel-surfing. Traditionally, a channel- 



WO 00/39707 ^ PCT/EP99rt0221 

14 

surfing user searches for a program of interest by randomly or systematically sampling a 
number of broadcast channels until one of the broadcast programs strikes the user's interest. 
By using the classification system 100 and retrieval system 150 in an on-line mode, a more 
efficient search for programs of interest can be effected, albeit with some processing delay. In 
5 an on-line mode, the story segment identifier 1 10 provides text segments 113, audio segments 
1 12, and key frames 1 14 corresponding to the current non-commercial portions of the 
broadcast channel. The classifier 120 classifies these portions using the techniques presented 
above. The filter 160 identifies those portions that conform to the user's preferences 191, and 
the presenter 170 presents the set of key frames 171 from each of the filtered portions 161. 

10 When the user selects a particular set of key frames 171, the broadcast channel selector 105 is 
tuned to the channel corresponding to the selected key frames 171, and the story segment 
identifier 110, storage device 1 15 and player 180 are placed in a bypass mode to present the 
video stream 101 of the selected channel to the display 175. 

As would be evident to one of ordinary skill in the art, the principles and 

15 techniques presented in this invention can include a variety of embodiments. FIG. 4 illustrates 
an example consumer product 400 in accordance with this invention. The product 400 may be 
a home computer or a television; it may be a video recoixling device such as a VCR, CD-R/W, 
or DVR device; and so on. The example product 400 records potentially interesting story 
segments 1 1 1 for presentation and selection by a user. The story segments 1 1 1 are extracted or 

20 indexed from a video stream 101 by the classification system 100, as discussed above with 
regard to FIG. 1. The video stream 101 is selected from a multichannel input 401, such as a 
cable or antenna input, via a selector 420 and tuner 410. 

In one embodiment of FIG. 4, the selector 420 is a programmable multi-event 
channel selector, such as found in conventional VCR devices. The user programs the selector 

25 420 to tune the tuner 410 to a particular channel of interest at each particular event time for a 
specified duration. For example, a user may program the time and duration of morning news 
on one channel, the evening news on another channel, and late night news on yet another 
channel. As each channel is subsequently selected by the selector 420, the stories 1 1 1 are 
segmented and stored on the recorder 430 via the classification system 100, which also 

30 classifies each segment 1 1 1 and extracts relevant key frames 171 for display on the 

input/output device 440, as discussed above. In a preferred embodiment, the recorder 430 is a 
continuous-loop recorder, or continuous circular buffer recorder, which automatically erases 
the oldest segments 1 1 1 as it records each of the newest segments 1 1 1, so as to continually 
provide as many recent ; segments 1 1 1 as it recording media allows. The user accesses the 



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system via the input/output device 440 and is presented the key frames of the most recent 
segments 111 that match the user's preferences; thereafter, the user selects segments 181 for 
display based on the presented key frames 171. ^ 

A number of optional capabilities are also illustrated in FIG. 4. To optimize the 
5 use of the available recording media, the retrieval system 150 may be configured to provide 
selective erasure, via 451, rather than the oldest-erasure scheme discussed above. When a new 
segment 111 requires an allocation of the recording media, the retrieval system 150 identifies 
the segments 111 that are on the recording media that have the least correlation with the user's 
preferences. Instead of replacing the oldest segments with the newest segments, the segments 

10 of least potential interest to the user are replaced by the newest segments. The retrieval system 
150 also terminates the recording of the newest segment when it determines, based on the 
classification of the newest segment by the classification system 100, that the newest segment 
is of no interest to the user, based on the user preferences. 

Also illustrated by dashed lines 191 and 402, the product 400 optionally 

15 provides for the selection of channels by the selector 420 via a prefilter 425. The prefilter 425 
effects a filtering of the segments 1 1 1 by controlling the selection of channels 401 via the 
selector 420 and tuner 410. As noted above, ancillary text information is commonly available 
that describes the programs that are to be presented on each of the channel of the 
multichannel input 401. As illustrated by the dashed lines, this ancillary information, or 

20 program guide, may be a part of the multichannel input 401, or via a separate program guide 
connection 402. Using techniques similar to those of filter 160, discussed above, the prefilter 
425 identifies the programs in the program guide 402 that have a strong correlation with the 
user preferences 191, and programs the selector 420 to select these programs for recording, 
classification, and retrieval, as discussed above. 

25 As would be evident to one of ordinary skill in the art, the capabilities and 

parameters of this invention may be adjusted depending upon the capabilities of each 
particular embodiment. For example, the product 400 may be a portable palm-top viewing 
device for commuters who have little time to watch live newscasts. The commuter connects 
the product 400 to a source of multichannel input 401 overnight to record stories 111 of 

30 potential interest; then, while commuting (as a passenger) uses the product 400 to retrieve 
stories of interest 181 from these recorded stories 111. In this embodiment, resources are 
limited, and the parameters of each component are adjusted accordingly. Fpr example, the 
number of key frames 1 14 associated with each segment 1 1 1 may be substantially reduced, the 
prefilter 425 or filter 160 may be substantially more selective, and so on. Similarly, the 



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classification 100 and retrieval systems 150 of FIG. 1 may be provided as standalone devices 
that dynamically adjusts their parameters based upon the components to which they are 
attached. For example, the classification system 100 may be a very large and versatile system 
that is used for classifying story segments for a variety of users, and different models of 
5 retrieval systems 150, each having different levels of complexity and cost, are provided to the 
users for retrieving selected story segments. 

The foregoing merely illustrates the principles of the invention. It will thus be 
appreciated that those skilled in the art will be able to devise various arrangements which, 
although not explicitly described or shown herein, embody the principles of the invention and 

10 are thus within its spirit and scope. For example, the key frames 1 14 have been presented 
herein as singular images, although a key frame could equi valently be a sequence of images, 
such as a short video clip, and the presentation of the key frames would be a presentation of 
each of these video clips. The components of the classification system 100 and retrieval 
system 150 may be implemented in hardware, software, or a combination of both. The 

15 components may include tools and techniques common to the art of classification and 

retrieval, including expert systems, knowledge based systems, and the like. Fuzzy logic, neural 
nets, multivariate regression analysis, non-monotonic reasoning, semantic processing, and 
other tools and techniques common in the art can be used to implement the functions and 
components presented in this invention. The presentor 170 and filter 160 may include a 

20 randomization factor, that augments the presentation of key frames 1 14 of segments 161 

having a high correspondence with the user preferences 191 with key frames 1 14 of randomly 
selected segments, regardless of their correspondence with the preferences 191. The source of 
the video stream 101 may be digital or analog, and the story segments 1 1 1 may be stored in 
digital or analog form, independent of the source of the video stream 101. Although the 

25 invention has been presented in the context of television broadcasts, the techniques presented 
herein may also be used for the classification, retrieval, and presentation of video information 
from sources such as public and private networks, including the Internet and the World Wide 
Web, as well. For example, the association between sets of key frames 1 14 and story segments 
1 1 1 may be via embedded HTML commands containing web site addresses, and the retrieval 

30 of a selected story segment 1 8 1 is via the selection of a corresponding web site. 

As would be evident to one of ordinary skill in the art, the partition of functions 
presented herein are presented for illustration purposes only. For example, the broadcast 
channel selector 105 may be an integral part of the story segment identifier 1 10, or it may be 
absent if the classification and retrieval system is being used to retrieve story segments from a 



WO 00/39707 




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17 



single source video stream, or a previously recorded video stream 101. Similarly, the story 
segment identifier 1 10 may process multiple broadcast channels simultaneously using parallel 
processors. The filter 160 and profiler 190 may be integrated as a single selector device. The 
key frames 1 14 may be stored on, or indexed from, the recorder 115, and the presenter 170 
functionality provided by the player 180. In like.manner, the extraction of key frames 114 
from the story segments 1 1 1 may be effected in either the story segment identifier 1 10 or in 
the presenter 170. These and other partitioning and optimization techniques will be evident to 
one of ordinary skill in the art, and within the spirit and scope of this invention. 



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CLAIMS: 



1. A video classification system (100) comprising: 

a story segment identifier (1 10) that processes a video stream (101) and 
partitions the video stream (101) into a plurality of story segments (111), and produces one or 
more key frames (1 14) that are associated with each story segment of the plurality of story 
segments (1 1 1), and 

a classifier (120), operably coupled to the story segment identifier (110), that 
associates one or more classifications (121) to each story segment of the plurality of story 
segments (1 11), to facilitate a selection among the plurality of story segments (111) based on 
the one or more classifications (121). 

2 - The video classification system (100) of claim 1, wherein: 

the video stream (101) includes an associated text stream (240), 

the story segment identifier (1 10) partitions the text stream (240) into an at least 

one text segment (241-244) corresponding to at least one each story segment (221-224) of the 

plurality of story segments (111), and 

the classifier (120) associates the one or more classifications (121) to the at 

least one each story segment (221-224) based on the at least one text segment (241-244). 

3 - The video classification system (100) of claim 1, wherein: 

the video stream (101) includes an associated audio stream (230), 

the story segment identifier (110) partitions the audio stream (230) into an at 

least one audio segment (231-234) corresponding to at least one each story segment (221-224) 

of the plurality of story segments (1 1 1), and 

the classifier (120) associates the one or more classifications (121) to the at 

least one each story segment (221-224) based on the at least one audio segment (231-234). 

4 - The video classification system (100) of claim 3, wherein 

the classifier (120) includes a converter that converts the at least one audio 
segment (231-234) into an at least one text segment (241-244) and the classifier (120) 



WO 00/39707 PCT/EP99/10221 

19 

associates the one or more classifications (121) to the at least one each story segment (221- 
224) based on the at least one text segment (241-244). 

5. The video classification system (100) of claim 1, wherein the story segment 

5 identifier (1 10) partitions the video stream (101) based on at least one of a recognized figure, a 
recognized scene, a video cut, and a detected commercial. 

6. The video classification system (100) of claim 1, wherein the one or more key 
frames (1 14) are determined based upon a transform of an encoding of the each story segment 

10 of the plurality of story segments (1 1 1). 

7 * The video classification system (100) of claim 1, further including 

a storage device (115) that stores the plurality of story segments (111). 

15 8. A retrieval system (150) for retrieving story segments of a plurality of story 

segments (11 1) based on one or more classifications (121) associated with each story segment 
of the plurality of story segments (1 1 1), the retrieval system (150) comprising: 

a filter (160) that identifies one or more filtered story segments (161) of the 
plurality of story segments (111) based on the one or more classifications (121) that are 
20 associated with each story segment, 

a presenter (170), operably coupled to the filter (160), that sequentially presents 
one or more key frames (1 14) that are associated with the one or more filtered story segments 
(161) on a display (175). 

25 9. A video device comprising: 

a classification device (100) that classifies a plurality of segments (1 1 1) of a 
video stream (101) by producing a classification (121) based on at least one of text, audio, or 
visual information associated with each segment of the plurality of segments (1 1 1), and 

a retrieval device (150) that facilitate a selection of an at least one each segment 
30 (181) of the plurality of segments (1 1 1) by matching the classification (121) of the at least one 
each segment (181) of the plurality of segments (111) to an at least one user preference (191), 
and by presenting an at least one key frame (171) of the at least one each segment (181) of the 
plurality of segments (111) on a display (175). 



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20 



10. A user interface for retrieving a selected segment ( 1 8 1) of a plurality of 

segments (1 1 1) of a video stream (101), comprising: 

a means for rendering (170) one or more key frames (1 14) associated with one or more 
segments (161) of the plurality of segments (111), and 

a means for selecting (178) the selected segment (181) based on the rendering of the one or 
more key frames (114). 



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1/3 








176 
v \ 


^175 




□ 
nr 




178 



FIG.1 



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3/3 




FIG. 3 




FIG. 4 



INTERNATION^SEARCH REPORT 



A CLASSIFICATION OP SUBJECT MATTER 

IPC 7 G06F17/30 

According to International Patent Classification QPCt or to both national classification and IPC 



It tatlOrtll Application No 

PCT/EP 99/10221 



B. FIELDS SEARCHED 



Minimum documentation searched (classification system followed by classification symbots) 

IPC 7 G06F 



Documentation searched other than minimum documentation to the extent that such aocuments are included in the fields searched 
Electronic data base consulted during (he International search (name of data base and. where practical, search terms used) 



C. DOCUMENTS CONSIDERED TO BE RELEVANT 





Citation ot document, with Indication, where appropriate, of the relevant pateages 


Relevant to daim No. 


X 


CHRISTEL, M., STEVENS, $., KANAOE , T. ET 
AL: "Techniques for the Creation and 
Exploration of Digital Video Libraries" 
MULTIMEDIA TOOLS AND APPLICATIONS 
vol. 2, 1996, XP002134742 
Boston, Kluwer Academic Publishers 
the whole document 


1-10 


X 


ARIKI Y ET AL: "A TV NEWS RETRIEVAL 
SYSTEM WITH INTERACTIVE QUERY FUNCTION" 


1,3-10 



CONFERENCE ON COOPERATIVE INFORMATION 

SYSTEMS, COOP IS, 24 June 1997 (1997-06-24) 

•XP000197416 

the whole document 

-/-- 



| X] Furtner documents are listed in the continuation of box C. 


^ | Patent family members are listed in annex. 


"A" document defining the general state of the art which is not 
considered to be of particular relevance 

" e " *f* i9r doaimmt but published on or after (he international 
filing date 

"L- document which may throw doubts on priority ctaim(s) or 
which (s crted to establish the publication date of another 
citation or other special reason (as specified) 

*0" document referring to an oral disclosure, use, exhibition or 
other means 

■P" document published prior to the International tiling date but 
later than the priority date d aimed 


T" later document published after the International filing date 
or priority date and not in conflict with the application but 
cited to understand the principle or theory underlying the 
invention 

"X" document of particular relevance; the claimed invention 
cannot be considered novel or cannot be considered to 
involve an inventive step when the document Is taken alone 

"Y" document of particular retevance; the claimed invention 

cannot be considered to involve an inventive step when the 
document is combined with one or more other such docu- 
ments, such combination being obvious to a person skilled 
in the art. 

document member of the same patent family 


Date of the actual completion of the international search ~~ 


Date of mailing of the international search report 


4 April 2000 


17/04/2000 


Name and mailing address of the ISA 

!ST2^ P 2W ? fflC8 ' PA WIS Patwttlaan 2 
NL - 2280 HV Riiswijk 

Tel. (+31-70) 340-2040. Tx. 31 651 epo nf, 

Fax: (+31-70) 340-3016 


Authorized officer 

Abbing, R 





page 1 of 2 



INTERNATION^SEARCH REPORT 



In *U3H5j Application No 

PCT/EP 99/10221 



C(Contlnuation) DOCUMENTS CONSIDERED TO BE RELEVANT 



Category - Citation of document, with indteation.where appropriate, ol the relevant passages 



Relevant lo claim No. 



HAUPTMANN A G ET AL: "Artificial 
Intelligence techniques 1n the Interface 
to a digital video library" 
HUMAN FACTORS IN COMPUTING SYSTEMS. CHI 97 
EXTENDED ABSTRACTS, PROCEEDINGS OF 1997 
ANNUAL INTERNATIONAL CONFERENCE ON HUMAN 
FACTORS IN COMPUTING SYSTEMS, ATLANTA , GA. 
USA, 22-27 MARCH 1997, pages 2-3, 
XP002134683 

1997, New York, NY, USA, ACM, USA 
ISSN: SBN 0-8979-926-2 
the whole document 

SMITH J R ET AL: "VISUALLY SEARCHING THE 
WEB FOR CONTENT" 

IEEE MULTIMEDIA, US, IEEE COMPUTER SOCIETY, 
vol. 4, no. 3, 1 July 1997 (1997-07-01), 
pages 12-20, XP000702058 
ISSN: 1070-986X 



1-7,10 



8,9 

1-7,10 



page 15, column 1, line 30 
column 1, line 19 
figure 3 



-page 16, 



SMITH M A ET AL: "VIDEO SKIMMING AND 
CHARACTERIZATION THROUGH THE COMBINATION 
OF IMAGE AND LANGUAGE UNDERSTANDING 
TECHNIQUES" 

PROCEEDINGS OF THE IEEE COMPUTER SOCIETY 
CONFERENCE ON COMPUTER VISION AND PATTERN 
RECOGNITION, US, LOS ALAMITOS, IEEE COMP. 
SOC. PRESS, 

vol. CONF. 16, 1997, pages 775-781, 
XP000776576 ISBN: 0-7803-4236-4 
the whole document 



8,9 



1-10 



Farm PCT/tS A/210 (contfruitkn of sacond sfcwt) (jmy igQ2) 



page 2 of 



2